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Risk-based fault detection using Self-Organizing Map
Citation
Yu, H and Khan, F and Garaniya, V, Risk-based fault detection using Self-Organizing Map, Reliability Engineering and System Safety, 139 pp. 82-96. ISSN 0951-8320 (2015) [Refereed Article]
Copyright Statement
Copyright 2015 Elsevier Ltd.
DOI: doi:10.1016/j.ress.2015.02.011
Abstract
The complexity of modern systems is increasing rapidly and the dominating relationships among system
variables have become highly non-linear. This results in difficulty in the identification of a system's
operating states. In turn, this difficulty affects the sensitivity of fault detection and imposes a challenge
on ensuring the safety of operation. In recent years, Self-Organizing Maps has gained popularity in
system monitoring as a robust non-linear dimensionality reduction tool. Self-Organizing Map is able to
capture non-linear variations of the system. Therefore, it is sensitive to the change of a system's states
leading to early detection of fault. In this paper, a new approach based on Self-Organizing Map is
proposed to detect and assess the risk of fault. In addition, probabilistic analysis is applied to characterize
the risk of fault into different levels according to the hazard potential to enable a refined monitoring of
the system. The proposed approach is applied on two experimental systems. The results from both
systems have shown high sensitivity of the proposed approach in detecting and identifying the root
cause of faults. The refined monitoring facilitates the determination of the risk of fault and early
deployment of remedial actions and safety measures to minimize the potential impact of fault
Item Details
Item Type: | Refereed Article |
---|---|
Keywords: | Risk Assessment, Fault Detection |
Research Division: | Engineering |
Research Group: | Chemical engineering |
Research Field: | Process control and simulation |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in the mathematical sciences |
UTAS Author: | Yu, H (Mr Hongyang Yu) |
UTAS Author: | Khan, F (Professor Faisal Khan) |
UTAS Author: | Garaniya, V (Dr Vikram Garaniya) |
ID Code: | 99465 |
Year Published: | 2015 |
Web of Science® Times Cited: | 24 |
Deposited By: | NC Maritime Engineering and Hydrodynamics |
Deposited On: | 2015-03-25 |
Last Modified: | 2017-11-01 |
Downloads: | 0 |
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